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Monte Carlo Stochastic Analysis of Fault Over-voltages Using SSN and the RT-LAB Python API

This demonstration makes a Monte-Carlo analysis of a small distribution grid with faults. It is a fully lumped network with many fault insertions. As there is no long transmission lines in this model, SSN is notably useful in this model because it puts switches in different SSN groups, without delays nor memory overflow and allows HIL simulation.

Refer to the Small distribution grid for relay testing documentation, located inside the Distribution Grid demos.

Demonstration

The following demonstration will show the user how to import the model into RT-LAB and run a python script which will run the simulation as many times as the user desires. The demonstration makes use of the snapshot feature of RT-LAB, where a single time point in the simulation can be reloaded, allowing the user to avoid having to always run the simulation from the beginning until steady-state conditions occur.


Please complete the following steps in order to run the script:

  • Open RT-LAB.

  • Double-click the Create New Project icon, enter a project name and select Next.





  • Select an empty template and click Finish.



  • Right-click the project that you have created and select Import...



  • Navigate to the folder .../demos/Advanced Applications/Monte Carlo/ located inside the ARTEMiS installation and import the Python (.py), Simulink Model (.mdl) and MATLAB script (.m) files in the directory (the html files are not needed).



  • Build the model for your choice of target.



  • Select the Filter Resources button in order to view the File System of your model workspace in the Project Explorer pane.



  • Select the Python script from the Project Explorer pane and double click it to view it.



  • Section 2 of the script allows the user to alter the fault location, the number of simulation runs, snapshot takes time and the simulation duration.



  • Right-click the "main_script.py" icon in the RT-LAB explorer in the python script and select Python→Run.

  • The script will now run, and the user can observe the statistic of the maximum voltages recorded updating in real time.



  • The user can update the Simulink model and the Python script to simulate different fault and other simulation conditions.

  • Below the simulation number has been changed to 1000 simulation runs.

References

C. Dufour, J. Mahseredjian, J. Belanger, "A Combined State-Space Nodal Method for the Simulation of Power System Transients", IEEE Transactions on Power Delivery, Vol. 26, no. 2, April 2011 (ISSN 0885-8977), pp. 928-935

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